Cargando…
Identification of Potential Key Genes in the Pathogenesis of Chronic Obstructive Pulmonary Disease Through Bioinformatics Analysis
Chronic obstructive pulmonary disease (COPD) is a common respiratory disease with high morbidity and mortality. The etiology of COPD is complex, and the pathogenesis mechanisms remain unclear. In this study, we used rat and human COPD gene expression data from our laboratory and the Gene Expression...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8595135/ https://www.ncbi.nlm.nih.gov/pubmed/34804123 http://dx.doi.org/10.3389/fgene.2021.754569 |
_version_ | 1784600130930868224 |
---|---|
author | Guan, Qingzhou Tian, Yange Zhang, Zhenzhen Zhang, Lanxi Zhao, Peng Li, Jiansheng |
author_facet | Guan, Qingzhou Tian, Yange Zhang, Zhenzhen Zhang, Lanxi Zhao, Peng Li, Jiansheng |
author_sort | Guan, Qingzhou |
collection | PubMed |
description | Chronic obstructive pulmonary disease (COPD) is a common respiratory disease with high morbidity and mortality. The etiology of COPD is complex, and the pathogenesis mechanisms remain unclear. In this study, we used rat and human COPD gene expression data from our laboratory and the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) between individuals with COPD and healthy individuals. Then, protein–protein interaction (PPI) networks were constructed, and hub genes were identified. Cytoscape was used to construct the co-expressed network and competitive endogenous RNA (ceRNA) networks. A total of 198 DEGs were identified, and a PPI network with 144 nodes and 355 edges was constructed. Twelve hub genes were identified by the cytoHubba plugin in Cytoscape. Of these genes, CCR3, CCL2, COL4A2, VWF, IL1RN, IL2RA, and CCL13 were related to inflammation or immunity, or tissue-specific expression in lung tissue, and their messenger RNA (mRNA) levels were validated by qRT-PCR. COL4A2, VWF, and IL1RN were further verified by the GEO dataset GSE76925, and the ceRNA network was constructed with Cytoscape. These three genes were consistent with COPD rat model data compared with control data, and their dysregulation direction was reversed when the COPD rat model was treated with effective-component compatibility of Bufei Yishen formula III. This bioinformatics analysis strategy may be useful for elucidating novel mechanisms underlying COPD. We pinpointed three key genes that may play a role in COPD pathogenesis and therapy, which deserved to be further studied. |
format | Online Article Text |
id | pubmed-8595135 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-85951352021-11-18 Identification of Potential Key Genes in the Pathogenesis of Chronic Obstructive Pulmonary Disease Through Bioinformatics Analysis Guan, Qingzhou Tian, Yange Zhang, Zhenzhen Zhang, Lanxi Zhao, Peng Li, Jiansheng Front Genet Genetics Chronic obstructive pulmonary disease (COPD) is a common respiratory disease with high morbidity and mortality. The etiology of COPD is complex, and the pathogenesis mechanisms remain unclear. In this study, we used rat and human COPD gene expression data from our laboratory and the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) between individuals with COPD and healthy individuals. Then, protein–protein interaction (PPI) networks were constructed, and hub genes were identified. Cytoscape was used to construct the co-expressed network and competitive endogenous RNA (ceRNA) networks. A total of 198 DEGs were identified, and a PPI network with 144 nodes and 355 edges was constructed. Twelve hub genes were identified by the cytoHubba plugin in Cytoscape. Of these genes, CCR3, CCL2, COL4A2, VWF, IL1RN, IL2RA, and CCL13 were related to inflammation or immunity, or tissue-specific expression in lung tissue, and their messenger RNA (mRNA) levels were validated by qRT-PCR. COL4A2, VWF, and IL1RN were further verified by the GEO dataset GSE76925, and the ceRNA network was constructed with Cytoscape. These three genes were consistent with COPD rat model data compared with control data, and their dysregulation direction was reversed when the COPD rat model was treated with effective-component compatibility of Bufei Yishen formula III. This bioinformatics analysis strategy may be useful for elucidating novel mechanisms underlying COPD. We pinpointed three key genes that may play a role in COPD pathogenesis and therapy, which deserved to be further studied. Frontiers Media S.A. 2021-11-03 /pmc/articles/PMC8595135/ /pubmed/34804123 http://dx.doi.org/10.3389/fgene.2021.754569 Text en Copyright © 2021 Guan, Tian, Zhang, Zhang, Zhao and Li. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Guan, Qingzhou Tian, Yange Zhang, Zhenzhen Zhang, Lanxi Zhao, Peng Li, Jiansheng Identification of Potential Key Genes in the Pathogenesis of Chronic Obstructive Pulmonary Disease Through Bioinformatics Analysis |
title | Identification of Potential Key Genes in the Pathogenesis of Chronic Obstructive Pulmonary Disease Through Bioinformatics Analysis |
title_full | Identification of Potential Key Genes in the Pathogenesis of Chronic Obstructive Pulmonary Disease Through Bioinformatics Analysis |
title_fullStr | Identification of Potential Key Genes in the Pathogenesis of Chronic Obstructive Pulmonary Disease Through Bioinformatics Analysis |
title_full_unstemmed | Identification of Potential Key Genes in the Pathogenesis of Chronic Obstructive Pulmonary Disease Through Bioinformatics Analysis |
title_short | Identification of Potential Key Genes in the Pathogenesis of Chronic Obstructive Pulmonary Disease Through Bioinformatics Analysis |
title_sort | identification of potential key genes in the pathogenesis of chronic obstructive pulmonary disease through bioinformatics analysis |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8595135/ https://www.ncbi.nlm.nih.gov/pubmed/34804123 http://dx.doi.org/10.3389/fgene.2021.754569 |
work_keys_str_mv | AT guanqingzhou identificationofpotentialkeygenesinthepathogenesisofchronicobstructivepulmonarydiseasethroughbioinformaticsanalysis AT tianyange identificationofpotentialkeygenesinthepathogenesisofchronicobstructivepulmonarydiseasethroughbioinformaticsanalysis AT zhangzhenzhen identificationofpotentialkeygenesinthepathogenesisofchronicobstructivepulmonarydiseasethroughbioinformaticsanalysis AT zhanglanxi identificationofpotentialkeygenesinthepathogenesisofchronicobstructivepulmonarydiseasethroughbioinformaticsanalysis AT zhaopeng identificationofpotentialkeygenesinthepathogenesisofchronicobstructivepulmonarydiseasethroughbioinformaticsanalysis AT lijiansheng identificationofpotentialkeygenesinthepathogenesisofchronicobstructivepulmonarydiseasethroughbioinformaticsanalysis |